Prediction of small molecule binding modes to macromolecules of known three-dimensional structure is a problem of paramount importance in rational drug design (the “docking”problem) . . . Protein binding sites exhibit highly selective recognition of small organic molecules, in that evolution has equipped them with a complex three-dimensional “lock” into which only specific “keys” will fit. This has been exploited by medicinal chemists in the design of molecules to selectively augment or retard biochemical pathways and so exhibit a clinical effect. X-ray crystallography has revealed the structure of a significant number of these binding sites. It would be advantageous in attempting the computer-aided design of therapeutic molecules to be able to predict and to explain the binding mode of novel chemical entities (the “docking” problem) when the active site geometry is known.” (Jones et al. J. Mol. Bio. 267, pg. 727 (1997)) With the advent of combinatorial chemistry and the resulting ability to synthesize large collections of compounds for a broad range of targets, it has become apparent that the capability to effectively prioritize screening efforts is crucial to the rapid identification of the appropriate region of chemical space for a given target. Since it has been generally observed that hits obtained against a given target are clustered in a finite region of chemical space, there is reason to believe that given the right computational tools it is possible to prioritize screening efforts such that only libraries containing active compounds are interrogated. Effective prioritization tools would allow scientists to both obtain leads in a cost effective and efficient manner and to test virtual libraries against novel targets prior to active synthesis and bioanalysis, thereby, reducing synthesis costs. With the expected flood of new targets becoming available in the coming decade, it will be critical to focus screening efforts on target appropriate regions of chemical space.
There are many challenges to overcome prior to being able to develop appropriate library prioritization tools. At one extreme are the screens for which there is no structural data for the target. In these cases, QSAR or other data mining tools are typically the method of choice for screening prioritization. At the opposite extreme are the structure-based approaches that rely on the availability of X-ray structures of the target. Unfortunately, in most cases, a crystal structure is not available. With the advent of proteomics and high-throughput protein crystallography, however, it is likely that for a given target, a structure of a related protein will be available. In these cases, a homology model can be built starting from the structure of a related protein, and structure-based tools could be utilized in conjunction with QSAR or other data mining tools.
When structural information for a target protein is available, molecular docking can be a useful tool for prioritizing screening efforts (reference: Charifson, P. S., ed. Practical Application of Computer-aided Drug Design 1997, Marcel Dekker: New York. 551; Knegtel, R. M. A. and M. Wagener, “Efficacy and Selectivity in Flexible Database Docking,” PROTEINS: Structure, Function and Genetics, 1999, Vol. 37, p. 334–345; and Debnath, A. K., L. Radigan, and S. Jiang, “Structure-based Identification of Small Molecule Antiviral Compounds Targeted to the gp41 Core Structure of the Human Immunodeficiency Virus Type 1,” Journal of Medicinal Chemistry, 1999, Vol. 42(17), p. 3202–3209). Operationally, this means that rather than assaying an entire collection of compounds, the compounds are first docked and ranked via some scoring function, and then only a subset of the compounds, usually the highest ranked, are assayed. This approach to prioritizing screening efforts usually increases by a factor of 1–10 the number of active compounds, i.e., when compared to a randomly selected subset of compounds, (see, Charifson, P. S., et al., “Consensus Scoring: A Method for Obtaining Improved Hit Rates From Docking Databases of Three-dimensional Structures Into Proteins,” Journal of Medicinal Chemistry, 1999, Vol. 42(25), p. 5100–5109).
The ultimate goal of this invention is to use molecular docking as a way to prioritize combinatorial library screening efforts, i.e., rather than ranking individual compounds, combinatorial libraries of compounds are ranked. Compounds synthesized through combinatorial methods are often quite flexible when compared to typical databases of compounds used for molecular docking studies. Thus, for a docking procedure to be useful, it should be able to handle fairly flexible compounds (as many as 10–20 rotatable bonds), and it should be extremely fast (on the order of one million compounds a week). With these constraints in mind, a new docking technique has been developed and validated, as presented hereinbelow.